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In recent times, shape of you lyrics sung by ed sheeran shape of you is written by ed has become increasingly relevant in various contexts. What does .shape [] do in "for i in range (Y.shape [0])"?. shape is a tuple that gives you an indication of the number of dimensions in the array. So in your case, since the index value of Y.shape[0] is 0, your are working along the first dimension of your array. arrays - what does numpy ndarray shape do? 82 yourarray.shape or np.shape() or np.ma.shape() returns the shape of your ndarray as a tuple; And you can get the (number of) dimensions of your array using yourarray.ndim or np.ndim().

it gives the n of the ndarray since all arrays in NumPy are just n-dimensional arrays (shortly called as ndarray s)) Difference between numpy.array shape (R, 1) and (R,). Shape n, expresses the shape of a 1D array with n items, and n, 1 the shape of a n-row x 1-column array. (R,) and (R,1) just add (useless) parentheses but still express respectively 1D and 2D array shapes, Parentheses around a tuple force the evaluation order and prevent it to be read as a list of values (e.g.

python - x.shape [0] vs x [0].shape in NumPy - Stack Overflow. Equally important, on the other hand, x.shape is a 2-tuple which represents the shape of x, which in this case is (10, 1024). x.shape[0] gives the first element in that tuple, which is 10. Here's a demo with some smaller numbers, which should hopefully be easier to understand. What does shape[0] and shape[1] do in python?

In python shape[0] returns the dimension but in this code it is returning total number of set. Equally important, please can someone tell me work of shape[0] and shape[1]? Code: m_train = train_set_x_orig.shape[0]

tensorflow placeholder - understanding `shape= [None,`. You can think of a placeholder in TensorFlow as an operation specifying the shape and type of data that will be fed into the graph.placeholder X defines that an unspecified number of rows of shape (128, 128, 3) of type float32 will be fed into the graph. a Placeholder does not hold state and merely defines the type and shape of the data to flow ... Combine legends for color and shape into a single legend. I'm creating a plot in ggplot from a 2 x 2 study design and would like to use 2 colors and 2 symbols to classify my 4 different treatment combinations.

Currently I have 2 legends, one for the colo... python - shape vs len for numpy array - Stack Overflow. Still, performance-wise, the difference should be negligible except for a giant giant 2D dataframe. So in line with the previous answers, df.shape is good if you need both dimensions, for a single dimension, len() seems more appropriate conceptually.

Looking at property vs method answers, it all points to usability and readability of code. Keras input explanation: input_shape, units, batch_size, dim, etc. For any Keras layer (Layer class), can someone explain how to understand the difference between input_shape, units, dim, etc.? For example the doc says units specify the output shape of a layer....